Standard closed-circuit television (CCTV) systems have long been used to monitor locations requiring security. Such CCTV systems remotely monitor buildings, military installations, infrastructure, industrial processes, and other sensitive locations. As real and perceived threats against persons and property grow, the list of locations requiring remote security monitoring also grows. For example, regularly unmanned infrastructure such as power substations, oil rigs, bridges, and so on, may now require protection through remote monitoring.
These traditional video surveillance systems may include networked video detectors, sensors, and other equipment connected to a central site. One of the drawbacks to such traditional monitoring systems is that they often rely on human supervision to view video images, interpret the images, and determine a relevant course of action such as alerting authorities. The high cost of manning such systems makes them impractical when a large number of remote sites require monitoring. Furthermore, a lack of automation in analysis and response increases response time and decreases reliability.
Known automated monitoring systems solve many of these problems. Such known automated systems digitally capture and stream video images, detect motion, and provide automatic alerts based on parameters such as motion, sound, heat and other parameters. However, these known automated systems often require large transmission bandwidths, provide only limited control over remote devices, remain sensitive to network issues, and struggle with accurate image and motion recognition.
Therefore, a need exists for reliable systems and methods of remote monitoring that require limited bandwidth, while providing accurate motion recognition and intelligent alert capabilities.